Making good financial decisions should be based on a thorough analysis that is free of influence from the use of behavioral biases or heuristics… or so we’re told. We should strive to adopt an objective point of view and choose the best path forward based on factual data, avoiding gut-instinct, rules of thumb, and other biases that could influence our behavior. This perspective has become so common that many financial advisors now market one of their key value-adds as their ability to 'de-bias' their clients and provide an objective point of view. While there are certainly cases where bias and heuristics can interfere with good client decision-making, is it possible that we’ve adopted too negative of a stance towards bias and heuristics when making financial decisions?
In this post, Derek Tharp – lead researcher at Kitces.com, and an assistant professor of finance at the University of Southern Maine – explores this question and the research summarized by Gerd Gigerenzer and Henry Brighton, which finds that not only can bias and heuristics be potentially valuable tools from a cost-benefit perspective, but they can, under the right circumstances, even improve decision-making beyond what could be achieved with extensive data collection and analysis. Of course, it has always been acknowledged that there is a cost associated with gathering and analyzing data. It’s no surprise that at some point the costs of further analyzing a decision are not worth the benefits. But the insight highlighted by Gigerenzer and Brighton is that, in some cases, less truly is more!
Under the right circumstances, bias and heuristics can help us make better decisions by allowing us to avoid 'overfitting' historical data and making the most efficient use of our limited cognitive resources. Similar to intuitively knowing how to catch a ball, a skill based on heuristics developed and ingrained over a long history of evolution and natural selection (despite the fact that no human can, in the moment, do the calculus necessary to compute a ball’s trajectory and then precisely position their body to complete the catch), some heuristic techniques allow us to ignore what otherwise might seem to be important factors, but still arrive at a solution not only equal to what we might have accomplished via a more cognitively demanding route, but actually better instead!
Interestingly, the conditions under which bias and heuristics are the most efficient (i.e., an environment where data is lacking, or where the data appears to be too random or 'noisy' to be considered useful) are precisely the conditions under which we make many financial decisions, which could explain why there are so many best practice ‘rules of thumb’ (e.g., the 10% savings rule, the 70% replacement ratio in retirement rule, and the ‘cost-per-use’ strategy to make purchasing decisions) that are still remarkably pervasive in society and effective in helping people achieve their financial goals.
Of course, there’s danger in relying on a rule of thumb that is inappropriate for one’s circumstances. Few people who start saving at 55 are going to be successful saving 10% of their income. But, at the same time, it’s possible that our attempt as financial advisors to rely on in-depth analyses of a client’s situation (and the use of parameters, such as safe withdrawal rates based on historical data) may 'overfit' a client’s situation and miss out on some of the wisdom embedded in heuristics and biased decision-making. This perspective may also help explain why, despite nearly consistent proclamations that Americans aren’t saving enough, no epidemic of elderly poverty has actually come to fruition. It’s possible, and there are studies which have found, that the failure to account for factors such as Social Security income in retirement or the declining spending throughout retirement have systematically overstated how much savings many Americans need.
Ultimately, though, the key point is that we’ve perhaps been too negative towards bias and heuristics. Bias and heuristics are not inherently good, but they aren’t inherently bad either. It is crucially important to acknowledge the ‘ecology’ in which heuristics and biased decision-making can be rational, as well as the environment in which greater data gathering and analysis may be useful. By effectively using (and refining) heuristic techniques when it is appropriate to do so, we can develop an arsenal of useful decision-making tools to better help our clients!
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